Regulatory Effects of the Uty/Ddx3y Locus on Neighboring Chromosome Y Genes and Autosomal Mrna Transcripts in Adult Mouse Non-Reproductive Cells

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Regulatory effects of the Uty/Ddx3y locus on neighboring chromosome Y genes and autosomal mRNA transcripts in adult mouse non-reproductive cells

Christian F. Deschepper

Cardiovascular Biology Research Unit, Institut de recherches cliniques de Montréal (IRCM) and Université de Montréal

Address : 100 Pine Ave West Montréal (QC) Canada H2W 1R7 E-mail : [email protected] Phone : 514 987 5759

ABSTRACT In addition to sperm-related genes, the male-specific chromosome Y (chrY) contains a class of ubiquitously expressed and evolutionary conserved dosage-sensitive regulator genes that include the neighboring Uty, Ddx3y and (in mice) Eif2s3y genes. However, no study to date has investigated the functional impact of targeted mutations of any of these genes within adult non-reproductive somatic cells. We thus compared adult male mice carrying a gene trap within their Uty gene (UtyGT) to their wild-type (WT) isogenic controls, and performed deep sequencing of RNA and genome-wide profiling of chromatin features in extracts from either cardiac tissue, cardiomyocyte-specific nuclei or purified cardiomyocytes. The apparent impact of UtyGT on gene transcription concentrated mostly on chrY genes surrounding the locus of insertion, i.e. Uty, Ddx3y, long non-coding RNAs (lncRNAs) contained within their introns and Eif2s3y, in addition to possible effects on the autosomal Malat1 lncRNA. Notwithstanding, UtyGT also caused coordinate changes in the abundance of hundreds of mRNA transcripts related to coherent cell functions, including RNA processing and translation. The results altogether indicated that tightly co-regulated chrY genes had nonetheless more widespread effects on the autosomal transcriptome in adult somatic cells, most likely due to mechanisms other than just transcriptional regulation of corresponding protein-coding genes.

INTRODUCTION Although the contributions of genes on the male sex chrY have long believed to be restricted to their effects on reproductive functions in sex organs, increasing evidence indicates that their impact may in fact extend to somatic cells as well. Thus, several types of genetic rodent models have shown that chrY and/or some of its genetic variants affect a range of phenotypes within the cardiovascular, immune, metabolic or neurologic systems1,2,3,4,5. In humans, one specific haplotype of the male-specific portion of chrY (MSY) associates with increased coronary artery disease risk, along with altered gene expression within macrophages6, while mosaic loss of chrY in blood cells (a relatively frequent and age-related event) associates with a host of disease manifestations, including shorter survival, increased cancer risk, cardiovascular events, Alzheimer disease and age-related macular degeneration7,8,9,10.

In addition of the male sex-determination Sry gene, MSY carries only a handful of protein-coding genes, which fall for the most part in two classes. The first one corresponds to genes expressed only in male reproductive tissues and/or specializing in sperm-related functions11,12. Genes within the second class share a particular set of properties, as they: i) are expressed ubiquitously in all tissues; ii) are X-degenerate genes that have on chromosome X (chrX) counterparts that escape chrX-inactivation in females; iii) exert bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

their effects in a dose-related fashion that depends on expression of copies from both sex chromosomes; and iv) belong to an evolutionary conserved core of genes found in MSY from all placental vertebrates12. Although there are some species-specific variation concerning the exact nature of genes found in that shared core group, some of them (including Uty, Ddx3y and Kdm5d) are common to all investigated species12.

In addition to the above properties, the X-degenerate genes on MSY have functional annotations that relate mostly to some of the most basic cell functions (such as chromatin modification, ubiquitination, translation, splicing and chromatin modification). To date, there is evidence (albeit limited) that X- degenerate genes on MSY show at least some level functional redundancy with their homologs on chrX. For instance, DDX3Y has been shown to be functionally interchangeable with DDX3X in cultured mammalian cells13,14. Likewise, studies using mice with inactivating gene traps of either Utx or Uty demonstrated that Uty showed high level of functional redundancy with Utx during development, with further tests showing that the effects of both genes were independent of any lysine demethylase activity15. In humans, overexpressed UTY has been shown to rescue preleukemic phenotypes induced by UTX deficiency, also in a manner that was independent of any lysine demethylase activity16. However, there is still no study to date exploring whether targeted mutations of MSY genes do have an impact on somatic non-reproductive cells in adult organisms. To address this particular question, we used male mice carrying an inactivating gene trap within the fourth intron of Uty (UtyGT in short). These mice were previously shown to be fully viable15, but not used for studying phenotypes other than those occurring during the developmental stage. In particular, we performed deep sequencing of RNA (RNA-Seq) in hearts and cardiomyocytes from either adult YUtyGT mice or their isogenic wild-type (WT) controls. The results were compared to those obtained with either a chromatin immunoprecipitation and sequencing (ChIP- Seq) assay of Histone H3 acetyl lysine-27 (H3K27ac) residues (i.e. marks of active enhancers) or with assays for transposase-accessible chromatin using sequencing (ATAC-Seq), which quantifies chromatin accessibility across the genome. We found that despite significant effects on hundreds of mRNA transcripts in cardiac cells, the genomic regulatory effects UtyGT were much more restricted, as they concentrated mostly on genomic regions on MSY. The data suggested that while the transcriptional effects of the Uty locus were restricted to a handful of regulators, the latter could nonetheless further regulate the transcriptomic profile of cells, presumably via post-transcriptional or post-translational mechanisms.

RESULTS

Regulatory effects of UtyGT on surrounding MSY genes and genomic sequences:

Combined analysis of the results of RNA-Seq, ChIP-Seq and ATAC-Seq demonstrated that the greatest impact of UtyGT was observed on either the abundance of transcripts from surrounding genes or chromatin marks in corresponding genomic regulatory regions. RNA-Seq revealed that Ddx3y and Eif2s3y were among the top most affected genes, either in terms of statistical significance or absolute fold change (Table 1). Ddx3y was the gene whose expression was (after Uty itself) affected most significantly, with its abundance in either hearts or cardiomyocytes from UtyGT being about  15% of that in their WT counterparts (Table 1). Eif2s3y was among the 60 most affected genes but its expression was (contrary to Ddx3y) increased in hearts or cardiomyocytes from UtyGT mice. RT-qPCR experiments were performed to further validate those results. Since Uty, Ddx3y and Eif2s3y are all ubiquitously expressed MSY genes, non-cardiac tissues (including skeletal muscle, spleen, liver and/or primary lung fibroblasts) were included in the analysis. Regardless of the type of tissue, Ddx3y showed (similarly as detected by RNA-Seq) a greater than five-fold downregulation in samples from UtyGT mice (Fig. 1a). Likewise, Eif2s3y was upregulated in all tested tissues, the abundance of its mRNA transcripts in UtyGT tissues being about 150% of that found in their WT counterparts (Fig. 1b). In additional experiments, we verified whether UtyGT had any effect on expression of the chrX homologs of the above genes. Expression of Utx was unaffected and Ddx3x showed a slight increase of about 10 % (P < 0.05); expression of Eif2s3x was increased by about 40% (P < 0.01) (Supplementary Fig S1).

To further test whether the impact of UtyGT could be found at the level of proteins as well, we took advantage of the fact that the protein sequences of mouse Ddx3x and Ddx3y show 92% identity with each other as well as with human DDX3X or DDX3Y, and used two distinct antibodies against human recombinant DDX3X for Western blot analyses. Data obtained with each antibody were pooled by normalizing all data by the average of the values obtained in material from females (Fig. 2). Left ventricles from male XYWT mice contained similar concentrations of overall Ddx3 immunoreactivity as that found in females; in contrast, the concentrations found in left ventricles from in male XYUtyGT mice was about 50% of that found in either male XYWT or female XX mice. Similar differences were observed in primary fibroblasts from male XYWT and XYUtyGT mice (Supplementary Fig S2). Altogether, the data indicated that the Ddx3y transcript was translated into a protein, and that its contribution to overall Ddx3 immunoreactivity was about equal as that of its chrX homolog Ddx3x. bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Genome-wide profiling of either H3K27ac marks or chromatin accessible regions was performed by ChIP- Seq and ATAC-Seq, respectively. In both cases, the most striking effects of UtyGT were observed in the vicinity of Uty and Ddx3y. With the H3K27ac ChIP-Seq, the regions showing the most highly significant differences in left ventricular chromatin from WT and UtyGT mice concerned two MSY peaks, i.e. one in the first exon region of Uty (FDR = 1.3E-27) and one in the first intron region of Ddx3y (FDR = 1.2E-27) (Fig.3). These peaks (detected in chromatin from WT mice, but not in that from their UtyGT counterparts) aligned with ENCODE-published adult mouse heart tracks for either H3K27Ac or p300 (two marks of active enhancers), DNase hypersensitive regions (another mark of accessible chromatin regions) or for Pol2 (a marker of active transcription initiation sites) (Fig. 3). The ATAC-Seq assays also detected differentially accessible regions in the proximal promoter region of Uty (FDR = 3.5 E-34) and the first intron of Ddx3y (FDR = 2.8 E-18) (i.e. regions overlapping with the positions of the two H3K27ac peaks described above), as well as in the proximal promoter of Eif2s3y (FDR = 5.50E-14) (Fig. 3).

Regulatory relationships between MSY genes:

In primary lung fibroblasts from UtyGT mice, Ddx3y is down-regulated to the same extent as in heart or other non-cardiac tissues (Fig. 1a). To test whether such low Ddx3y levels could be rescued by re-initiation of expression of the protein-coding part of Uty, we thus infected such cells with viral particles carrying a lentiviral expression vector containing CMV-driven sequences for both Uty and the reporter eGFP gene, and isolated Uty-overexpressing cells by eGFP cytofluorometry. We found that Uty was clearly overexpressed in eGFP-positive cells, but that is was not associated with any changes in the low levels of Ddx3y expression (Fig. 4).

To test whether MSY genes could display high levels of co-expression constitutively, we used tools provided by the COEXPRESdb database to analyze data obtained on multiple tissues with a total of total 2236 Affymetrix arrays across 154 experiments23. Among all 21036 tested gene transcripts tested, Uty was found to interact most strongly with the protein coding Ddx3y, Eif2s3y and Uba1y genes, as well as with two other gene products: i) Gm39552, a three-exon lncRNA gene located within intron 25 of Uty; and ii) and C030026M15Rik, which corresponds to expressed sequences from Uty intron 14 (Supplemental Table 1). No autosomal gene showed co-expression scores approaching those found for MSY genes.

Since steady-state mRNA levels in cell cytoplasm are influenced by a variety of post-transcriptional mechanisms, it has been proposed that deep-sequencing of nuclear RNA (nucRNA-Seq) provides data that are more closely related to true transcriptional output24,25. We thus performed nucRNA-Seq on part of the nuclear material that was otherwise used for ATAC-Seq. Initial results indicated that the only bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

transcripts affected significantly (FDR < 0.05) were those encoded by Uty, Ddx3y, and Gm4017, the latter being annotated as a processed pseudogene located within Ddx3y intron 17 (ENSMUSG00000101059). This intronic localization was reminiscent to that observed for Gm39552 and C030026M15Rik (i.e. the two transcripts reported as co-expressed with Uty in the COEXPRESdb database). Visual inspection of the nucRNA-Seq sequencing tracks showed that these two transcripts could indeed be observed in samples from WT cardiomyocyte nuclei. However, unlike Gm4017, potential changes in their expression levels could not have been detected by the nucRNA-Seq as it was performed, because their coordinates were not included in the standard ENSEMBL mus GRCm38 gene build annotation file. We thus performed a novel nucRNA-Seq analysis that used a custom annotated file where the positions of Gm39552 and C030026M15Rik were manually added to the GRCm38 gene build, in addition to that of AK153586, a previously detected expressed RNA transcript whose sequence matched genomic sequences within Uty intron 4 (Supplemental Fig. S3). When using these additional parameters, all transcripts emerged as significantly decreased (FDR < 0.05) in samples from UtyGT mice (Table 2). The presence of these transcripts in material from WT cardiomyocyte nuclei was further supported by the fact that FPKM values obtained in corresponding genomic regions were significantly higher (P < 0.05) than values found in remaining intron sequences from the genes they were inbedded in. In contrast, none of these transcripts were detected by the RNA-Seq analysis of cardiomyocyte extracts, where RNA originates predominantly from the cytoplasm.

Effects of UtyGT on autosomal chromatin:

Outside of MSY, the H3K27ac ChIP-Seq analysis detected only two autosomal regions with significant differences. The first one comprised three peaks on chr17 (with matching positions of ENCODE tracks for H3K27Ac, p300, Pol2 and DNase hypersensitivity) whose intensity was lower in UtyGT hearts than in their WT counterparts (Supplementary Fig. S4). However, neither RNA-Seq results nor additional RT-qPCR experiments performed on heart extracts (results not shown) showed any evidence of differential expression for any of the genes in the proximity of these peaks (Dynlt1b, Tmem181a, Tmem181b, and the lncRNA gene Gm29719). The second peak was found in a gene-poor intergenic region on chr15, with no matching peak within published ENCODE tracks.

With ATAC-Seq, differently accessible regions in autosomal chromatin were detected chr19 (in the intergenic regions between the long non-coding RNA (lncRNA) gene Malat1 and Neat1 (FDR = 9.6E-19) (Fig.5) (Supplemental Table2). This signal was matched by increased expression of Malat1 in UtyGT samples was found in heart samples by RNA-Seq, and further confirmed by RT-qPCR, both for heart as bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

well as non-cardiac tissues (including skeletal muscle, liver and primary fibroblasts) (Fig. 6). We detected no change in expression of the Malat1-neighboring Neat1 gene, either by RNA-Seq or additional RT-qPCR experiments (results not shown). Increased chromatin accessibility (FDR 1.E-31) was also found on chr5 in the region of the first intron of En2. However, we found no evidence indicating that the corresponding transcript was present in our samples, a finding in keeping with ENCODE transcriptome data showing that expression of this gene is mostly restricted to the developing central nervous system. In addition to En2 and Malat1, some levels of differential accessibility were detected for about 100 other autosomal regions (Supplemental Table 2). However, the level of significance of other differentially accessibility regions dropped sharply compared to the top five most significantly affected regions, and there was no accompanying evidence for differential regulation of nearby genes.

Impact of UtyGT on the adult heart transcriptome:

The RNA-Seq experiments revealed that UtyGT was accompanied: i) in whole heart left ventricles, by down- and upregulation of 671 and 716 genes (FDR < 0.05), with absolute fold changes averaging 0.52 and 0.68 fold, respectively; and ii) in adult cardiocytes, by down- and upregulation of 669 and 476 genes (FDR < 0.05), with absolute fold changes averaging 0.49 and 0.63 fold, respectively. A total of 151 genes were common to both datasets. To test whether the transcriptomic changes could concern particular cellular functions, we looked for GO ontology terms showing significant enrichment (FDR < 0.01) among the UtyGT- affected genes (FDR < 0.05) with > 2-fold enrichment, then regrouped the terms meeting these criteria within broader categories that could encompass them. Among genes down-regulated in UtyGT mice, highly enriched GO terms could be consolidated with 2-3 overarching categories, accounting for 59% and 70% of GO terms enriched in differentially expressed genes in left ventricles and cardiomyocytes, respectively (Table 3)(Supplemental Table S6). Likewise, among genes up-regulated in UtyGT mice, enriched GO terms could be consolidated with 3-5 overarching categories, accounting for 45% and 50% of all enriched GO terms in left ventricles and cardiomyocytes, respectively (Table 4)(Supplemental Table S6). Both in ventricular extracts and isolated cardiomyocytes, genes up-regulated in UtyGT mice showed high and significant enrichment for ribosome-related GO terms.

DISCUSSION:

Despite mounting correlative evidence that MSY genes have effects outside of reproductive tissues, studies using gene targeting experiments to demonstrate in a direct fashion their impact within adult somatic cells and/or their mechanisms of action are still lacking. The current study demonstrates that a bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

gene trap within the Uty gene does have demonstrable effects within adult somatic cell functions, but also that MSY genes may have some idiosyncratic properties. The most prominent effect of the UtyGT gene trap is that it is accompanied by a profound and ubiquitous downregulation of its neighboring Ddx3y gene and, by a smaller extent, by up-regulation of its other flanking gene (Eif2s3y). The dual effects of UtyGT on expression of both Uty and Ddx3y were accompanied by direct regulatory genomic changes involving a disappearance of both H3K27Ac and ATAC-Seq peaks in the proximal enhancer regions of these two genes. In contrast, the protein-coding product of the Uty gene did not appear to have direct regulatory actions on Ddx3y expression, because its re-expression in UtyGT primary cells did not alleviate the downregulation of Ddx3y. One possible explanation for these observations (for which there is actually some support within the literature) could be that non-coding sequences within the Uty/Ddx3y locus actually play a role in the co-regulation of these two genes. Indeed, comparisons of chrY sequences from 5 mammalian species have revealed that, despite highly divergent gene order among all of them, the Uty/Ddx3y gene pair is part of a microsyntenic region that has been preserved over 340 million years of independently sampled evolutionary history26. Other phylogenomic studies have shown previously that: i) such conserved ancient microsyntenic pairs arise when conservation of cis-regulatory sequences was required for co-regulation of the genes, and ii) such sequences were enriched within non-coding regions of the locus, and often resided within particularly large introns of the genes within the conserved pair27. In fact, our nucRNA-Seq analysis revealed that 4 transcripts corresponding to genomic sequences within 3 introns of Uty and one of Ddx3y could indeed be detected in nuclei from WT mice, with some of them having been previously been detected in transcriptomic studies performed across a wide range of tissues and whose results have been compiled in publically available databases. In the present study, we also observed that abundance of all these non-coding transcripts was greatly decreased in nuclei from UtyGT mice cardiomyocytes. It thus appeared that the disappearance of H3K27ac and ATAC-Seq peak in the proximal enhancer regions of Uty and Ddx3y was accompanied by downregulation of not only the protein- coding parts of these genes, but also of transcripts originating from sequences within their introns.

In a more general fashion, the co-expression databases showed that high levels of co-expression were a defining feature of MSY genes in general. As this occurred not only in mice, but in humans as well, it may constitute an evolutionary conserved characteristic of MSY genes in vertebrates. Of note, such patterns of co-expression between neighboring genes are rarely seen within vertebrate genomes, and do almost never occur at such high levels28. Nonetheless, such characteristics may have emerged within the male chrY because evolutionary forces that are different from those exerted on autosomes29 have resulted in different types of regulatory mechanism. One other evolutionary conserved feature appeared to be that, bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

among the most highly co-expressed MSY genes, a high proportion of them [4 out of 8 of genes (50%) in mice, and 15 out of 23 (65%) in humans] were in fact non-coding. Interestingly, a recent study analyzing transcripts in brains from human and chimpanzee embryos discovered six novel non-annotated lncRNAs originating from chrY. Such RNA transcripts may thus constitute a class of agents that mediate some MSY effects or, alternatively, participate to the high levels of co-expression among MSY genes. Indeed, while three-dimensional looping events might be invoked in mice (where all X-degenerate MSY genes are contained within a relatively small 1 MB genomic region) as possible mechanisms underlying high levels of co-expression among MSY genes, such mechanisms are less likely to occur in humans, where the loci of MSY genes show much greater dispersion across much larger regions. Moreover, we found that the non-coding RNAs co-expressed with Uty were detected in samples from cardiomyocyte nuclei but not in those extracted from whole cardiomyocytes, indicating that these transcripts correspond in fact nuclear lncRNAs. The latter are known to participate (among other biological processes) to chromatin organization and accessibility, in part via recruitment of chromatin-modulating proteins to nearby chromatin regions30. In particular, given that UtyGT resides within the same Uty intron that harbors AK153586, decreased production of the latter could constitute one initial event triggering other chromatin rearrangements within the whole locus.

Although DDX3Y has been shown to be functionally interchangeable with DDX3X in cultured mammalian cells13,14, some controversy remains concerning the production of the cognate protein outside of reproductive tissues. Indeed, some have argued that the production of the DDX3Y protein was (in contrast to the ubiquitous expression of the gene) restricted to the male germline31,32. In contrast, other studies have detected DDX3Y peptides in either neural progenitor or hematopoietic stem cells33,34,35. Our Western blot analysis are in line with the latter studies, providing evidence that Ddx3y can indeed be translated into a protein in at least mouse somatic cells. Moreover, the downregulation of Ddx3y caused by UtyGT is accompanied by an equivalent reduction in overall Ddx3 immunoreactivity. The importance of this finding is many-fold. For instance, it has been shown that hematopoietic loss of DDX3X results is lethal in developing females, but viable in males36; however, without knowing whether production of the DDX3Y protein can occur in somatic cells, it was not possible to determine whether this compensatory effect of MSY could be due to DDX3Y itself. Likewise, since the actions of DDX3X are dosage-related, confirmation of the production of DDX3Y protein supports its possible contribution to dose-related effects. Of note, due to differences in their promoters, the DDX3Y and DDX3X genes have been shown to be independently regulated13, indicating that male organisms may regulate overall DDX3 immunoreactivity in part via mechanisms that are different from those in females. bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

When the results of H3K27ac ChIP-Seq, ATAC-Seq, RNA-Seq and nucRNA-Seq are all considered collectively, the genes contained within the Uty/Ddx3y locus were the only ones for which evidence for transcriptional regulation via direct regulatory genomic effects was entirely consistent across experiments. For Malat1, increased chromatin accessibility was matched by increased abundance of mRNA abundance in tissue extracts, but not in nuclear extracts. For Eif2s3y, the results were more difficult to interpret, as decreased chromatin accessibility in its proximal promoter region was matched by a trend towards decreased abundance in nuclear extracts (Table 2), which contrasted with a significant (FDR < 0.01) increase in the abundance of its transcript in tissues (see discussion below). Other indications of effects of UtyGT on either H3K27ac abundance or accessibility in autosomal chromatin were not matched by evidence for changes in the abundance of the transcripts of genes in corresponding regions. While the direct transcriptional effects of UtyGT thus appeared to be relatively restricted, the gene trap nonetheless had substantial effects on the transcriptome of cardiac cells, as hundreds of mRNA transcripts showed differential abundance. The magnitudes of the average fold-changes (ranging from 0.49 to 0.62) were relatively modest, but within the range of those reported by others that have studied sex biases in gene expression37,38. Moreover, there was functional coherence in the transcript abundance changes, as GO term analyses revealed that the majority of terms showing enrichment in differentially regulated genes showed great overlap within a few well-defined functional categories. For genes downregulated in left ventricles of UtyGT mice, these functions corresponded to post-translational protein processes (including protein localization, oligomerization and phosphorylation) and maintenance of intracellular membranes (including organelles, mitochondria and sarcolemma). For genes upregulated in left ventricles of UtyGT mice, these functions corresponded to ribosomal activity (including ribosomal organization and translation), processing and metabolism of RNA, and chromosome maintenance. Overall, these functional categories are compatible with the proposed concept that MSY X-degenerate genes are regulators of some of the most basic cellular homeostatic maintenance mechanisms12. More specifically, the categories related to ribosomal activity and RNA processing might partly explain the somewhat contradictory results obtained for Eif2s3y. Indeed, the RNA-Seq of left ventricular extracts indicated that, in addition to increased Eif2s3y, the transcripts of three other eukaryotic initiation factors (Eif3a, Eif4e3, and Eif5) were significantly increased, whereas those of three others (Eif4g1, Eif3f, and Eif3h) were significantly decreased (FDR < 0.01). Accordingly, UtyGT might affect the stability of several eukaryotic initiation factor transcripts, and affect that of Eif2s3y in a manner that is contrary to its effects on transcription of the gene. bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Interestingly, at least two of the genes for which we observed evidence of increased transcription are known regulators of post-transcriptional mechanisms. On one hand, the DDX3 proteins are RNA helicases genes involved in all aspects of RNA metabolism, including mRNA nuclear export, translation and decay, and ribosome biogenesis39, 40. In particular, they affect protein translation by a variety of mechanisms that include interactions with translation initiation factors41,42, assembly of functional ribosomes43 and N6- methyladenosine modifications44, 45. On the other hand, Malat1 may regulate: i) mRNA transcript stability via its ability to behave as a miRNA-binding competitive endogenous RNA; and ii) regulate the activity of proteins and/or assist in their cellular localization via its direct protein-binding capabilities46. All these functions are related to the GO categories showing highest levels of enrichment among UtyGT-regulated gene transcripts (i.e. to ribosomal activity and RNA processing). The above two genes may even work in complementary fashion, as DDX3 regulates the abundance of N6-methyladenosine residues in Malat1, which in turn may modulate its biological activity44,47.

Altogether, the current study shows that MSY genes have demonstrable effects on regulators of adult somatic cell functions. However, such effects might result from MSY behaving as an entire integrated regulatory unit rather than from individually regulated MSY genes, and might involve mechanisms other than just transcriptional regulation of autosomal protein-coding genes. These findings could constitute a stepping stone to better understand in which fashion chrY-related genetic differences may affect health- related outcomes.

ACKNOWLEDGEMENTS

The work was partly funded by grant MOP-93583 from the Canadian Institutes for Health Research (CIHR). We are deeply grateful for the help of the IRCM Bioinformatics, Molecular Biology, Cytofluorometry and Animal Physiology Core Laboratories, and acknowledge in particular the contributions of Virginie Calderon, Caroline Grou, Odile Neyret, Myriam Rondeau, Éric Massicotte, Julie Lord and Manon Laprise. We also thank Sylvie Picard for technical help, and Mariana Bego and Mélanie Laporte for help with generation of lentiviral particles, and Pierre Bensidoun for immunocytochemistry and microscopy.

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MATERIAL AND METHODS

Mouse strains and cells.

All procedures involving mice were conducted following approval by the animal ethic committee of the Institut de Recherches Cliniques de Montréal (IRCM) and in agreement with the guidelines of the Canadian Council for Animal Care. UtyGt(XS0378)Wtsi (YUtyGT in short) ES cells (derived from the original parental E14Tg2a.4 ES cell line from 129P2/OlaHsd mice) were obtained from the Mutant Mouse Resource & Research Centers (MMRRC) and injected into C57BL/6J host blastocysts for chimera generation. Male chimeras were crossed to female C57BL/6J to assess germline transmission, and resulting males harboring the YUtyGT were mated for more than 10 generations to female C57BL/6J mice. Isogenic control WT mice were generated by backcrossing 129P2/OlaHsd male mice to female C57BL/6J mice for the same number of generations. Primary fibroblasts were obtained from lungs of adult mice as described previously49. When cells reached confluence six days after initial plating, they were split 1:4 for passage 1 (P1) and allowed to reach confluence again. For experiments, all fibroblasts were passage 2. Mouse adult cardiocytes were obtained by digesting adult mouse hearts by retrograde perfusion of a solution of collagenase type 2 (Worthington, Lakewood, NJ) in calcium-free solutions, followed by gravity sedimentation within 5% bovine serum albumin (BSA) solutions supplemented in a step-wise fashion with increasing CaCl2 concentrations, as described 50. After isolation, the cells were plated on laminin-coated dishes, and used 4 hours after plating for RNA isolation.

Isolation and flow-cytometry sorting of cardiomyocyte nuclei.

Cardiomyocyte-specific nuclei were isolated from frozen left ventricular cardiac sample as described 51,25, with modifications to optimize maintenance of RNA integrity. In short, left ventricle tissue (priorly powdered under liquid nitrogen) was homogenized with a Polytron in a 40 mM Tris / 10 mM citrate buffer (to inhibit ribonucleases52) containing 5 mM KCl, 12% polyethylene glycol 8000 (to allow for isolation of nuclei in the absence of ribonuclease-activating ions 53), 1 mM DTT, 1 mM PMSF, protease inhibitors, 1.5 mM spermine and 20 mM sodium propionate (for chromatin integrity). The extracts were processed with a Dounce homogenizer and passed sequentially through 98 µm and 38 µm cell selectors. After spinning, the nuclei were resuspended in 1 ml of the same buffer supplemented with 3µl of an Alexa fluor 642- bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

coupled antibody raised against the pericentriolar 1 protein (PCM1) (SCBT, Dallas, TX), i.e. an antigen that accumulates specifically around nuclei from cardiomyocytes51. A sub-aliquot of that material was used for counterstaining with Hoechst bis-benzidine. After 30 min incubation at 4°C, the pellets were washed and resuspended in 1 ml of Tris/acetate buffered saline supplemented with 2% ribonuclease-free BSA, sorted out by cytofluorometry, and collected in tubes containing 200U of the Ribolock ribonuclease inhibitor (Thermofisher). The numbers of nuclei isolated in this manner were 50,000 and 150,000 for ATAC-Seq and RNA-Seq, respectively. Parallel analysis of the Hoechst-counterstained sub-aliquots showed that > 95% of PCM1 positive particles were Hoechst-positive nuclei, and comprised in average about 30% of all nuclei in the preparation.

Sequencing-based procedures:

Total RNA was isolated from tissues and cells using RNeasy micro kits with in-column DNase treatments (Qiagen, Toronto, Canada). For cardiac left ventricular samples (n = 7 for each mouse strain), preparation of 3′ end RNA sequencing libraries were prepared (using the Lexogen QuantSeq 3′ mRNA-Seq Library Prep Kit FWD library) and sequenced by the Neuroscience Genomics Core. Read-quality confirmation and alignment on the mouse GRCm38/mm10 genome were performed using Lexogen’s QuantSeq Bluebee analysis platform. For RNA from isolated adult cardiomyocytes (n = 3 for each mouse strain), ribodepletion was performed using the Fast Select mouse RNA removal kit (Qiagen), the RNA-seq libraries were prepared according to manufacturer’s instructions using the Illumina TruSeq Stranded mRNA Kit and 50 bp single reads sequencing was performed with the Illumina HiSeq 4000 Sequencer. For the smaller amounts of RNA obtained from cardiomyocyte nuclei (n = 3 for each mouse strain), RNA-seq library preparation was performed using the SMARTer Stranded Total RNA-Seq Kit v2 - Pico (Takara Bio, Mountain View, CA) prior to 100 bp paired-end sequencing. For the last two sequencing analyses, after assessing the read quality using FastQC 0.11.8, alignment on the mouse GRCm38/mm10 genome was performed using STAR 2.5.1b. For all RNA-seq data, feature quantification was extracted with featureCounts v1.6.0 on the GRCm38 v98 Ensembl annotation. We also quantified additional transcript in the Uty region (AK142197, AK153586, Gm39552 and C030026M15) as there were not included in the Ensembl reference annotation. Differential expression analysis was performed with DESeq2 1.22.2 R package. For the nucRNA-Seq analysis, additional steps were taken to exclude artifactual contamination with genomic DNA. In particular, we identified a total of 2 megabases of regions where the absence of transcription was assessed on the basis of the following two overlapping criteria: i) lack of data showing expression of bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

corresponding transcripts in hearts (on the basis of mouse ENCODE transcriptome data), in contrast to other non-cardiac tissues where the pattern of tissue expression was restricted to just a few tissue types; and ii) lack of data for chromatin accessibility in the same regions, on the basis of ENCODE Dnase hypersensitivity tracks obtained in mouse adult hearts. UCSC exons and introns of these regions were extracted with GenomicFeatures R package and quantified as FPKM values with featureCounts. Absence of genomic contamination was confirmed by verifying that FPKM values were either zero or very low (Supplemental Table S6).

ChIP-Seq was performed on two replicate samples from each mouse strain as we described previously 54, using the ChIP grade ab4729 anti-H3K27 antibody from Abcam (Cambridge, MA). For the analysis, read quality was confirmed using FastQC 0.11.8 before alignment using Bowtie2 2.2.6 on the mouse GRCm37/mm9 genome (that latter build was chosen in order to allow for comparisons with other ChIP tracks published by ENCODE). Peak calling and differential enrichment were performed using the MACS2 2.0.10 “callpeaks” and “bdgdiff” functions, respectively. For ATAC-Seq, preparations containing 50,000 nuclei from either WT or UtyGT hearts were performed on three different days, and processed as described previously55. For the analysis, sequences from the adapters (NexteraPE-PE) were removed with Trimmomatic 0.36 after read quality control. Alignment was performed as for ChIP-Seq post-processing to remove PCR duplicates (Picard tool 2.4.1) and reads mapping to mitochondrial DNA (samtools 1.8). In order to represent the real Tn5 transposase binding sites of 9bp, the coordinates of the reads were shifted by 4bp for the plus strand and by 5bp for the minus strand, using Deeptools 3.0.1. The former was also used to remove ENCODE's blacklisted regions (signal artefact regions) and convert Bam files to BEDPE format. MACS2 was used to identify significant peaks using q-value < 0.01. Diffbind 2.10.0 R package was used to generate the count matrix of Tn5 insertion site numbers for each consensus peak (peaks that were present in at least 2 samples). Differentially accessibility regions (DARs) were identified between conditions using edgeR R package 3.24.3, including its generalized linear model functionalities to perform a multi-factor analysis to control for batch effects.

Data deposition:

Results from all the sequencing-based experiments were deposited in the Gene Expression Omnibus database as SuperSeries GSE147652.

Molecular biology.

Full-length mUty cDNA was obtained by PCR amplification of reverse-transcribed mouse heart RNA, then subcloned into the pIRES-V5 vector (gift of N. Seidah). After full sequence verification, the whole cDNA was subcloned into the lentiviral CMV GFP destination vector 736-1 (Addgene #19732), and further used along with packaging vectors to generate lentiviral particles (control lentiviral particles were generated in the same manner using empty lentiviral vectors). For infection, confluent P1 mouse fibroblasts were passaged at a concentration of 50,000 cells / 2 cm2 wells. Twenty four hours after replating, the cells were exposed for 6 hours to lentiviral particles (M.O.I. = 3) in growth medium supplemented with 6 µg/ml dextran sulfate, then washed and grown further overnight. Cell were then trypsinized for cytofluorometric separation of GFP-positive (i.e. cells with lentiviral integration) and GFP-negative cells. A total of 40-60,000 cells were then used for each sample to extract total RNA using the RNeasy micro RNA kit.

RT-qPCR was performed on cDNA obtained from total RNA using the High-Capacity cDNA Reverse Transcription Kit (ThermoFisher), using the primers detailed in Supplementary Table S3. Results were expressed as relative expression ratios of the 2(-Ct) values of the gene of interest vs. of that of the Rps16 normalizing gene.

Western blotting

After separation of gels and transfer to PVDF membranes, the latter were incubated with the following primary antibodies: monoclonal anti DDX3 C4, raised against the 114 N-terminal portion of human DDX3x (Santa Cruz Biotehcnology); polyclonal anti DDX3, raised against recombinant human DDX3x (Genetex, Irvine, CA); polyclonal anti GAPDH (Proteintech, Rosemont, IL). After treatment with horse radish peroxidase coupled second antibodies, signal was revealed by chemiluminescence, then visualized and analyzed using the Image lab software (Bio-Rad Laboratories, Saint-Laurent, QC, Canada).

Table 1: Effects of UtyGT on abundance of transcripts from MSY genes (KO/WT) and significance of the effects in either left ventricles or dispersed isolated adult cardiomyocytes

Left ventricles Dispersed cardiocytes

Uty Ddx3y Eif2s3y Uty Ddx3y Eif2s3y

KO/WT 5.4% 17.1% 323% 1.2% 15.8% 466%

FDR 1.2 E-40 6.6 E-37 4.7E-06 1.0E-97 2.9E-89 9.7E-48

Rank FDR 1 2 59 1 2 4

Rank abs. FC 1 3 18 1 7 16

KO/WT: ratios of the FKPM values obtained for UtyGT mice vs. that of WT mice; FDR: false discovery rate; Rank FDR: relative rank for FDR values obtained for all tested genes; Rank abs. FC: relative rank for absolute fold values obtained for all tested genes

Table 2: Top most differentially abundant RNA transcripts detected by the nucRNA-Seq analysis with custom annotation parameters

Ensembl gene ID Gene name mRNA gene_biotype localization KO/WT P-value P-adj (FDR)

ENSMUSG00000068457 Uty protein_coding MSY 0.02 2.02E-135 6.03E-131

AK153586 AK153586 expressed seq Uty intron 4 0.00 1.08E-15 1.23E-11

Gm39552 lncRNA Uty intron 25 0.00 1.24E-15 1.23E-11

C030026M15Rik AK049876 lncRNA Uty intron 14 0.00 1.54E-11 1.14E-07

ENSMUSG00000069045 Ddx3y protein_coding MSY 0.16 1.97E-09 1.17E-05

ENSMUSG00000101059 Gm4017 processed_pseudogene Ddx3y intron 17 0.13 7.31E-05 3.63E-01

ENSMUSG00000068745 Mybphl protein_coding Chr3 0.26 1.65E-04 6.71E-01

ENSMUSG00000069049 Eif2s3y protein_coding MSY 0.64 1.92E-04 6.71E-01

ENSMUSG00000056673 Kdm5d protein_coding MSY 0.69 2.03E-04 6.71E-01

Table 3: Common themes encompassing GO terms showing both high (> 2 fold) and significant (FDR < 0.01) enrichment among genes downregulated in UtyGT mice

Left ventricles Cardiomyocytes

# of GO % of GO Mean # of GO % of GO Mean Common theme Common theme terms. terms. FE terms. terms. FE

56 100 % Total  261 100 % Total 

17 30 % Post-translational fate of proteins 2.6 107 41 % Organo- / morpho-genesis 4.6

16 Organization of intracellular 29 % 4.3 41 16 % Responses to EC stimuli 4.8 membrane structures Cell migration / 35 13 % proliferation / 4.1 contacts

More details about each specific GO term and statistical values for their enrichment are present in Supplemental Table S6.

Table 4: Common themes encompassing GO terms showing both high (> 2 fold) and significant (FDR < 0.01) enrichment among genes upregulated in UtyGT mice

Left ventricles Cardiomyocytes

# of GO % of GO Mean # of GO % of GO Mean Common theme Common theme terms. terms. FE terms. terms. FE

111 100 % Total  224 100 % Total 

20 Mitochondrial 18 % Ribosomal activity 6.7 42 18 % 7.5 activity 18 Muscle contractile 16 % RNA processing 3.3 36 16 % 5.9 apparatus

12 11 % Chromosome maintenance 3 14 6 % Protein catabolism 4.8

13 6 % Ribosome organization 7.3

13 6 % Cytoskeleton

More details about each specific GO term and statistical values for their enrichment are present in Supplemental Table S6.

FIGURE LEGENDS:

Fig.1: RT-qPCR quantification of abundance of mRNA transcripts of Ddx3y (Fig. 1a) or Eif2s3y (Fig. 1b). The experiments were performed using extracts from either cardiac left ventricles, skeletal muscle, liver, spleen or primary lung fibroblasts from either WT or UtyGT mice. Relative expression values corresponded to the ratios of Delta Ct values obtained for the gene of interest vs. those obtained for the Rps16 normalizing gene.

Fig.2: Western blot analyses of global Ddx3 immunoreactivity. The experiments were performed using left ventricular extracts from either female XX, male XYUtyWT or male XYUtyGT hearts. The experiments were performed using anti-DDX3 antibodies from either Santa Crux Biotechnologies (top right part) or Genetex (bottom right part. Results from each analysis were quantified and normalized by the average of values obtained in females and combined (right part). Full images of the hybridized membranes are provided in Supplementary Fig. S5 and Supplementary Fig. S6.

Fig. 3: Graphic representation of results from the H3K27ac ChIP-Seq and ATAC-Seq analyses in MSY regions. Results represent those obtained within the genomic regions of the Uty locus and its two flanking genes. RefSeq gene coordinates are shown on top. Peaks for either H3K27ac ChIP-Seq or ATAC-Seq are shown in either the top or bottom framed areas, respectively. The areas framed in green indicate highlight peaks detected in WT, but not in UtyGT mice. All detected peaks align with those published by ENCODE (in red) and obtained using extracts from adult mouse hearts for either H3K27ac, p300 or Pol2 ChIP-Seq or Dnase hypersensitivity assays.

Fig.4: RT-qPCR quantification of abundance of mRNA transcripts of Uty (left) or Ddx3y (right). Experiments were performed in primary lung fibroblasts from UtyGT mice,em and infected with lentiviral particles containing lentiviral expression vectors that were either empty (CTL) or contained the full-length sequence of mouse Uty. In the latter case, the cells were sorted out by cytofluorometry to separate those with or without lentiviral integration (GFP positive or negative, respectively).

Fig.5: Graphic representation of results from ATAC-Seq analyses in chr19 regions. ATAC-Seq signals in cardiomyocyte nuclei from either WT or UtyGT mice (n = 3 in each group). The figure shows the intergenic bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

region between the genes Neat1 (partial coordinates shown at the bottom) and Malat1 (located further downstream, coordinates outside of the boundaries of the window). Fig.6: RT-qPCR quantification of abundance of Malat1 mRNA transcripts in four different tissues from WT and UtyGT mice. Malat1 expression is significantly increased (as determined by t-tests) in either left ventricles, liver and primary lung fibroblasts (*P < 0.05, **P < 0.01, ***P < 0.001, respectively) from UtyGT mice. A similar trend is observed in skeletal muscle, but did not reach statistical significance. bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Fig.1: RT-qPCR quantification of abundance of mRNA transcripts of Ddx3y (Fig. 1a) or Eif2s3y (Fig. 1b).

Fig.1a Ddx3y Ddx3y Ddx3y Ddx3y (left ventr.) (skeletal) (spleen) (fibroblasts)

1.5 1.5 0.20 0.3

o i

s 0.15

s 1.0

e 1.0 0.2

p x

e 0.10 ***

e v

i 0.5

t 0.5 0.1

a *** l 0.05 ***

e *** r 0.0 GT 0.0 0.00 0.0 WT Uty WT UtyGT WT UtyGT WT UtyGT Fig.1b Eif2s3y Eif2s3y Eif2s3y Eif2s3y (left ventr.) (liver) (spleen) (fibroblasts) 0.8 4 5 0.25

n 0.20 o 4 3

i 0.6

s s

e * r 3 0.15 ** ** p 0.4 2

x * e

e 2 0.10

v i t 1

a 0.2 l

e 1 0.05 r

0.0 0 0 0.00 GT GT WT UtyGT WT UtyGT WT Uty WT Uty

Fig.2: Western blot analyses of global Ddx3 immunoreactivity.

C o m b in e d v a lu e s (n o r m a liz e d to a v e r a g e o f X X ) XX XYwt XYUtyGT 2 .0

75 kDa Ddx3

h 1 .5 d

p 37 kDa Gapdh

a G

1 .0

3 wt UtyGT

x XX XY XY

d * * *

D 0 .5 75 kDa Ddx3

0 .0 37 kDa Gapdh w t U tyG T X X X Y X Y

Fig. 3: Graphic representation of results from the H3K27ac ChIP-Seq and ATAC-Seq analyses in MSY regions.

Fig.4: RT-qPCR quantification of abundance of mRNA transcripts of Uty (left) or Ddx3y (right).

Uty expression Ddx3y expression

50 40

T C

C 30

a t

t 20

l e

e 20

D D 10 10

0 0 CTL WT UtyGT UtyGT CTL WT UtyGT UtyGT (GFP neg) (GFP pos) (GFP neg) (GFP pos)

Fig.5: Graphic representation of results from ATAC-Seq analyses in chr19 regions.

Fig.6: RT-qPCR quantification of abundance of Malat1 mRNA transcripts in four different tissues from WT and UtyGT mice.

Malat1 Malat1 Malat1 Malat1 (left ventricles) (skeletal) (liver) (fibroblasts) 5.0 4 12 8

o o

o 10

i i

4.5 i 3 6

r r

* r ***

p p

p 8

x x

4.0 x 2 4

t t

t 6

l l

3.5 l 1 2

r r 4 3.0 0 0 GT GT GT WT Uty WT Uty WT UtyGT WT Uty

SUPPLEMENTARY FILES

Regulatory effects of the Uty/Ddx3y locus on neighboring chromosome Y genes and autosomal mRNA transcripts in adult mouse non-reproductive cells

Christian F. Deschepper

Cardiovascular Biology Research Unit, Institut de recherches cliniques de Montréal (IRCM) and Université de Montréal

Supplementary tables:

Supplementary Table S1: List of mouse genes with highest levels of co-expression with Uty, ranked on the basis of mutual ranking (MR) scores

Supplementary Table S2: Top most differentially accessible regions in chromatin from cardiomyocyte nuclei from either WT of UtyGT mice, as determined by ATAC-Seq assays. Regions formatted in bold correspond to those identified in the context of other experiments. Regions with FDR significance < E-09 are shown only if they are flanked by other regions with some levels of significance.

Supplementary Table S3: List of human genes with highest levels of co-expression with Uty, as determined on the basis of mutual ranking (MR) scores. Genes are shown in shaded cells when other neighboring genes also show evidence of interaction with UTY. Supplemental Table S4: Coordinates of genomic regions predicted to be transcriptionally silent in cardiomyocytes. The negligeable FPKM values obtained for these regions in samples from either YUtyGT mice or WT mice (identified as either Uty* or b6*) were interpreted as evidence for the absence of DNA contaminationin the nuclear RNA samples.

Supplementary Table S5: List of oligomer primers used for RT-qPCR amplification

Supplementary Table S6 is provided in an additional file as a four tab-containing Excel spreadsheet. Each sheet lists all GO terms showing both high (> 2 fold) and significant (FDR < 0.01) enrichment among genes affected by UtyGT (either down- or upregulated) in either left ventricles (LV) or cardiomyocyocytes (CM).

Supplementary Table S7 is provided in an additional file as a four tab-containing Excel spreadsheet. It contains information about genes showing either up- or down-regulation in left ventricles from UtyGT mice, as well as a more comprehensive list of GO categories showing significant enrichment for these genes. bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Supplementary Table S8 is provided in an additional file as a four tab-containing Excel spreadsheet. It contains information about genes showing either up- or down-regulation in cardiomyocytes from UtyGT mice, as well as a more comprehensive list of GO categories showing significant enrichment for these genes.

Supplementary figures:

Supplementary Fig. S1: RT-qPCR quantification of abundance of mRNA transcripts of Utx, Ddx3x and Eif2s3x in left ventricular extracts from UtyGT and WT mice. Expression of Utx was unaffected, Ddx3x showed a slight increase of about 10 % (*P < 0.05), expression of Eif2s3x was increased by about 40% (P < 0.01).

Supplementary Fig. S2: Western blot analysis of primary fibroblasts from either UtyGT and WT mice. Upper part: signal obtained with anti-DDX3 antibodies from Genetex; bottom part: signal obtained with anti-GAPDH antibodies.

Supplementary Fig. S3: Localization of loci embedded within introns of either Uty or Ddx3y and containing sequences corresponding to putatively expressed transcripts.

Supplemental Fig S4: Graphic representation of ATAC-Seq results for chr17. Regions shown contain peaks showing significant differences in intensity between UtyGT and WT mice. For comparison, ENCODE tracks obtained using extracts from adult mouse hearts for either H3K27ac, p300 or Pol2 ChIP-Seq or Dnase hypersensitivity assays are also shown (in red). Loci of known genes are shown in the top part of the figure (in blue).

Supplemental Fig S5: Full images of the hybridized membranes that have been used for the top part of Fig. 2 in the manuscript.

Supplemental Fig S6: Full images of the hybridized membranes that have been used for the bottom part of Fig. 2 in the manuscript.

Supplementary Table S1: List of mouse genes with highest levels of co-expression with Uty, ranked on the basis of mutual ranking (MR) scores

Rank Gene Chr Gene type Entrez Gene ID MR protein 0 Uty chrY:1,097,144-1,245,718 coding 22290 0

protein 1 Ddx3y chrY:1,260,771-1,286,629 coding 26900 2.13

protein 2 Eif2s3y chrY:1,010,543-1,028,594 coding 26908 2.26

protein 3 Kdm5d chrY:897,790-946,316 coding 20592 2.28

4 Gm39552 chrY:1,114,067-1,120,066 lncRNA 105243746 25.03

5 C030026M15Rik chrY:1,161,073-1,162,805 lncRNA 77378 116.33 protein 6 Uba1y chrY:2,264,257-2,278,687 coding 22202 218.38

7 Gm35612 chrX:50,537,389-50,562,598 lncRNA 102639259 750.5 protein 8 Usp9y chrY:1,298,961-1,459,782 coding 107868 1590.67

9 4932431L22Rik chrY:70,367,444-70,370,583 lncRNA 619557 2289.96

Co-expression values are expressed as “mutual ranking scores”, which corresponded to the mean geometric mean of the correlation rank of gene A to gene B and of gene B to gene A. Calculations were performed with tools provided by COEXPRESdb, using data from 2236 Affymetrix arrays (microarray platform GPL1261) performed on multiple tissues across 154 experiments. A detailed list of all tissues used is available at the following link: (https://coxpresdb.jp/static/help/GPL1261v2_samples.shtml). The MR scores are inversely proportional to the strength of co-expression levels (the lower the score, the stronger the interaction). MR scores higher than 200 are considered as weak.

Supplementary Table S2: Top most differentially accessible regions in chromatin from cardiomyocyte nuclei from either WT of UtyGT mice, as determined by ATAC-Seq assays.

Gene Name Chr Start End FDR Uty chrY 581836 582382 Promoter-TSS 3.50E-34 En2 chr5 28495275 28496134 First intron 1.02E-31 Ddx3y chrY 622332 623154 First intron 2.86E-18 Eif2s3y chrY 346529 347077 Promoter-TSS 5.50E-14 Malat1 chr19 5821944 5823927 Intergenic 9.64E-19 Neat1 chr19 5824319 5825012 TTS 8.61E-13 Neat1 chr19 5831054 5832841 Non-coding 2.23E-09 Neat1 chr19 5838441 5842512 Non-coding 8.52E-09

Neat1 chr19 5828977 5829566 Non-coding 1.12E-08

Neat1 chr19 5829981 5830325 Non-coding 3.04E-07

Neat1 chr19 5837107 5838143 Non-coding 1.43E-06

Neat1 chr19 5835340 5836037 Non-coding 2.01E-06

Neat1 chr19 5833417 5833811 Non-coding 2.73E-04

Myh7 chr14 55619384 55620431 Promoter-TSS 1.60E-09 Myh7 chr14 55620990 55624433 Intergenic 1.16E-06 Myh7 chr14 55612681 55615300 Intergenic 2.74E-06 Myh7 chr14 55608473 55609053 Intron 12 of 40 4.91E-05 Myh7 chr14 55615784 55616173 Intergenic 1.78E-03 Myh7 chr14 55606934 55608000 Intron 15 of 40 1.86E-02

Zbtb16 chr9 48632529 48633073 5.69E-09 Zbtb16 chr9 48574572 48575021 1.91E-05 Zbtb16 chr9 48564539 48564746 2.63E-04 Zbtb16 chr9 48590823 48591848 4.93E-04 Zbtb16 chr9 48605695 48605938 7.61E-04 Zbtb16 chr9 48568245 48568945 2.21E-02 Zbtb16 chr9 48636958 48637403 2.73E-02 Zbtb16 chr9 48622674 48623269 4.43E-02

Plin4 chr17 56242595 56246147 2.13E-08 Plin4 chr17 56239471 56241031 1.88E-06 bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.180232; this version posted July 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Supplementary Table S3: List of human genes with highest levels of co-expression with Uty,as determined on the basis of mutual ranking (MR) scores

Entrez Rank Symbol chr Gene type Gene ID MR 0 UTY chrY:13,248,379-13,480,673 protein coding 7404 0 5 DDX3Y chrY:12,904,868-12,920,478 protein coding 8653 16.89 1 USP9Y chrY:12,662,368-12,860,802 protein coding 8287 7.45 6 TTTY15 chrY:12,662,367-12,692,224 lncRNA 64595 23.11

2 KDM5D chrY:19,705,417-19,744,939 protein coding 8284 9.64 3 TXLNGY chrY:19,588,609-19,593,602 pseudo-gene 246126 11.07 17 LOC107987345 chrY: 19,039,939 – 19,049,347 pseudogene 107987345 388.97 18 BCORP1 chrY:19,456,394-19,567,092 pseudogene 286554 431.15 15 LOC105377223 chrY:19,552,934-19,563,950 lncRNA 105377223 342.69

4 ZFY chrY:2,966,844-3,002,626 protein coding 7544 12.12 21 ZFY-AS1 chrY:2,966,844-3,002,626 lncRNA 100506003 828.15

7 EIF1AY chrY:20,575,776-20,593,154 protein coding 9086 39.88 11 TTTY10 chrY:20,464,916-20,575,497 lncRNA 246119 105.32 20 LOC107987347 chrY:21,240,255-21,302,707 lncRNA 107987347 711.98 22 LOC105377225 chrY:21,138,363-21,170,221 lncRNA 105377225 1037.03

8 PRKY chrY:7,274,313-7,371,868 protein coding 5616 75.99 9 CYorf15B chr1:32,179,675-32,198,285 protein coding 84663 84.83 12 NLGN4Y chrY:14,523,967-14,622,220 protein coding 22829 106.44 13 TMSB4Y chrY:13,703,899-13,706,024 lncRNA 9087 120.78 14 LINC00278 chrY:3,002,894-3,120,705 lncRNA 100873962 255.24 16 NCRNA00185 chrY:18,872,501-18,878,228 lncRNA 55410 343.25 24 FAM224A chrY:18,326,253-18,353,210 lncRNA 401630 3018.95 19 TBL1Y chrY:6,910,686-7,091,683 lncRNA 90665 608.41 23 PCDH11Y chrY:5,056,090-5,104,700 lncRNA 83259 2602.03

Supplemental Table S4

ensembl_gene_id Coordinates mm10 length (bp) b6_11 b6_15 b6_31 uty_11 uty_15 uty_31

ENSMUSG00000008789 chr7:17,713,252-17,761,121 47,870 bp 0.00 0.00 0.00 0.00 0.00 0.00

ENSMUSG00000019785 chr10:33,512,334-33,624,600 112,267 bp 0.00 0.00 0.00 0.00 0.00 0.00

ENSMUSG00000020633 chr12:28,437,795-28,548,337 110,543 bp 0.00 0.00 0.00 0.00 0.00 0.00

ENSMUSG00000000560 chr5:70,961,057-71,095,849 134,793 bp 0.04 0.07 0.13 0.10 0.11 0.06

ENSMUSG00000001260 chr5:70,751,047-70,842,617 91,571 bp 0.00 0.00 0.00 0.00 0.00 0.00

ENSMUSG00000018589 chrX:165,129,017-165,326,981 197,965 bp 0.00 0.00 0.00 0.00 0.00 0.00

ENSMUSG00000022112 chr14:115,092,215-116,525,192 1,432,978 bp 0.00 0.00 0.00 0.00 0.00 0.00

ENSMUSG00000017688 chr3:3,508,030-3,659,800 151,771 bp 0.00 0.00 0.00 0.00 0.00 0.00

ENSMUSG00000022076 chr14:96,105,265-96,519,034 413,770 bp 0.00 0.00 0.00 0.00 0.00 0.00

ENSMUSG00000009356 chr11:87,806,428-87,826,114 19,687 bp. 0.00 0.00 0.00 0.00 0.00 0.00

ENSMUSG00000021363 chr13:41,025,120-41,079,706 54,587 bp 0.00 0.00 0.00 0.00 0.00 0.01

ENSMUSG00000005493 chr3:153,857,141-153,906,138 48,998 bp 0.18 0.10 0.15 0.22 0.10 0.22

ENSMUSG00000010505 chr2:181,763,332-181,827,775 64,444 bp 0.00 0.00 0.00 0.00 0.00 0.00

ENSMUSG00000004231 chr19:44,757,394-44,837,871 80,478 bp 0.00 0.00 0.00 0.00 0.01 0.00

ENSMUSG00000021852 chr14:49,298,520-49,525,837 227,318 bp 0.00 0.00 0.00 0.01 0.01 0.00

ENSMUSG00000010435 chr8:12,573,049-12,600,738 27,690 bp 0.00 0.00 0.00 0.00 0.00 0.00

ENSMUSG00000003271 chr7:45,729,983-45,759,555 29,573 bp 0.00 0.01 0.00 0.00 0.00 0.00

ENSMUSG00000001670 chr8:109,990,436-109,999,804 9,369 bp 0.00 0.00 0.00 0.00 0.00 0.00

ENSMUSG00000021541 chr13:56,773,098-56,895,789 122,692 bp 0.00 0.00 0.00 0.00 0.00 0.03

Supplementary Table S5: List of oligomer primers used for RT-qPCR amplification

Gene Forward Reverse Rps16 GCTACCAGGGCCTTTGAGATG AGGAGCGATTTGCTGGTGTGG Uty ATGGAGAAGGGCATGAGAAC AGTTGGTGGTCTTGGAGGTG Ddx3y GTGCCTTCTTGGTTGGAAAG AATCCAGCATTTGCAGAACC Eif2s3y AGGAGGCAGAGTTAGTGCAG CTTCTTATCTGGCCCCAACC Utx TGAAAGTTCCAGGAAGCAGAA TTCAAAACACCCCAGTAGCC Ddx3x GGAAGATATGGCCGTCGTAAA GACGGACTCTAGATCGGTATGA Eif2s3x GGGAGGTGTAGCTGGTGGTA GTTCCGCAAAAAGTGACACA

Supplementary Fig. S1:

Expression of Utx, Ddx3x and Eif2s3x in left ventricles from UtyGT and WT mice

Utx in LV Ddx3x in LV Eif2s3x in LV 1.5 2.0 1.2

n o i *

s **

s 1.0 1.5 0.8

x e

e v

i 0.5 1.0 0.4

a l

e r 0.0 0.5 0.0 WT UtyGT WT UtyGT WT UtyGT

Supplementary Fig. S2:

wt UtyGT XY XY

75 kDa Ddx3

37 kDa Gapdh

Primary fibroblasts

Supplemental Fig S3:

Ddx3y intron 17 Uty intron 25 Uty intron 14 Uty intron 4

Gm39552 AK153586 Gm4017

C030026M15Rik

Supplemental Fig S4:

Supplemental Fig. S5:

SCBT antibody left ventricles

Ddx3

Gapdh

For this membrane, Ddx3 hybridization was performed as a first step, and Gapdh hybridization was performed after stripping the signal from the membrane.

Supplemental Fig. S6:

Genetex antibody left ventricles

Ddx3

Gapdh

This membrane was cut in 2 parts at the 50 kDa mark: the top part was used for Ddx3 hybridization, the bottom part was used for Gapdh